Overview

Dataset statistics

Number of variables14
Number of observations514
Missing cells1865
Missing cells (%)25.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory59.4 KiB
Average record size in memory118.3 B

Variable types

Categorical2
Text4
DateTime2
Numeric4
Unsupported2

Dataset

Description기업구분,기업구분명,업체명,대표자성명,설립일자,정규직수,비정규직수,직원수,업종코드,업종코드명,주소,년도_정렬,등록일시,수정일시
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21056/S/1/datasetView.do

Alerts

기업구분 is highly overall correlated with 정규직수 and 2 other fieldsHigh correlation
기업구분명 is highly overall correlated with 정규직수 and 2 other fieldsHigh correlation
정규직수 is highly overall correlated with 직원수 and 2 other fieldsHigh correlation
직원수 is highly overall correlated with 정규직수 and 1 other fieldsHigh correlation
년도_정렬 is highly overall correlated with 직원수 and 2 other fieldsHigh correlation
정규직수 has 376 (73.2%) missing valuesMissing
비정규직수 has 514 (100.0%) missing valuesMissing
업종코드 has 279 (54.3%) missing valuesMissing
등록일시 has 182 (35.4%) missing valuesMissing
수정일시 has 514 (100.0%) missing valuesMissing
주소 has unique valuesUnique
비정규직수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
수정일시 is an unsupported type, check if it needs cleaning or further analysisUnsupported
직원수 has 376 (73.2%) zerosZeros

Reproduction

Analysis started2024-05-11 05:41:09.219423
Analysis finished2024-05-11 05:41:13.513853
Duration4.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기업구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
ssc
332 
src
182 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowssc
2nd rowssc
3rd rowssc
4th rowssc
5th rowssc

Common Values

ValueCountFrequency (%)
ssc 332
64.6%
src 182
35.4%

Length

2024-05-11T14:41:13.604612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:41:13.754122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ssc 332
64.6%
src 182
35.4%

기업구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
서울형 강소기업
332 
하이서울브랜드 기업
182 

Length

Max length10
Median length8
Mean length8.7081712
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울형 강소기업
2nd row서울형 강소기업
3rd row서울형 강소기업
4th row서울형 강소기업
5th row서울형 강소기업

Common Values

ValueCountFrequency (%)
서울형 강소기업 332
64.6%
하이서울브랜드 기업 182
35.4%

Length

2024-05-11T14:41:13.923040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:41:14.073931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울형 332
32.3%
강소기업 332
32.3%
하이서울브랜드 182
17.7%
기업 182
17.7%

업체명
Text

Distinct513
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-05-11T14:41:14.389943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length7.4007782
Min length3

Characters and Unicode

Total characters3804
Distinct characters399
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique512 ?
Unique (%)99.6%

Sample

1st row㈜롤리조쓰컴퍼니
2nd row㈜인티그레이션
3rd row㈜샐러디
4th row설로인 주식회사
5th row㈜테온
ValueCountFrequency (%)
주식회사 147
 
21.6%
㈜ 8
 
1.2%
풍림무약㈜ 2
 
0.3%
㈜페프 1
 
0.1%
미창(아랑주 1
 
0.1%
창의메디칼㈜ 1
 
0.1%
㈜유신모자 1
 
0.1%
㈜아이템홀릭 1
 
0.1%
㈜다산에이디 1
 
0.1%
모젼스랩㈜ 1
 
0.1%
Other values (515) 515
75.8%
2024-05-11T14:41:15.048512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 293
 
7.7%
176
 
4.6%
이 176
 
4.6%
주 175
 
4.6%
스 171
 
4.5%
사 163
 
4.3%
회 154
 
4.0%
식 152
 
4.0%
아 72
 
1.9%
트 61
 
1.6%
Other values (389) 2211
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3243
85.3%
Other Symbol 293
 
7.7%
Space Separator 176
 
4.6%
Close Punctuation 20
 
0.5%
Open Punctuation 20
 
0.5%
Uppercase Letter 20
 
0.5%
Lowercase Letter 14
 
0.4%
Decimal Number 12
 
0.3%
Other Punctuation 5
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 176
 
5.4%
주 175
 
5.4%
스 171
 
5.3%
사 163
 
5.0%
회 154
 
4.7%
식 152
 
4.7%
아 72
 
2.2%
트 61
 
1.9%
에 60
 
1.9%
리 47
 
1.4%
Other values (352) 2012
62.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
 
10.0%
E 2
 
10.0%
L 2
 
10.0%
S 2
 
10.0%
R 1
 
5.0%
G 1
 
5.0%
Y 1
 
5.0%
W 1
 
5.0%
X 1
 
5.0%
C 1
 
5.0%
Other values (6) 6
30.0%
Lowercase Letter
ValueCountFrequency (%)
a 3
21.4%
s 2
14.3%
l 2
14.3%
e 1
 
7.1%
b 1
 
7.1%
o 1
 
7.1%
i 1
 
7.1%
n 1
 
7.1%
t 1
 
7.1%
d 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 6
50.0%
0 2
 
16.7%
3 2
 
16.7%
6 1
 
8.3%
2 1
 
8.3%
Other Symbol
ValueCountFrequency (%)
㈜ 293
100.0%
Space Separator
ValueCountFrequency (%)
176
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3536
93.0%
Common 234
 
6.2%
Latin 34
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 293
 
8.3%
이 176
 
5.0%
주 175
 
4.9%
스 171
 
4.8%
사 163
 
4.6%
회 154
 
4.4%
식 152
 
4.3%
아 72
 
2.0%
트 61
 
1.7%
에 60
 
1.7%
Other values (353) 2059
58.2%
Latin
ValueCountFrequency (%)
a 3
 
8.8%
s 2
 
5.9%
l 2
 
5.9%
A 2
 
5.9%
E 2
 
5.9%
L 2
 
5.9%
S 2
 
5.9%
R 1
 
2.9%
e 1
 
2.9%
b 1
 
2.9%
Other values (16) 16
47.1%
Common
ValueCountFrequency (%)
176
75.2%
) 20
 
8.5%
( 20
 
8.5%
1 6
 
2.6%
. 5
 
2.1%
0 2
 
0.9%
3 2
 
0.9%
- 1
 
0.4%
6 1
 
0.4%
2 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3243
85.3%
None 293
 
7.7%
ASCII 268
 
7.0%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 293
100.0%
ASCII
ValueCountFrequency (%)
176
65.7%
) 20
 
7.5%
( 20
 
7.5%
1 6
 
2.2%
. 5
 
1.9%
a 3
 
1.1%
s 2
 
0.7%
l 2
 
0.7%
A 2
 
0.7%
E 2
 
0.7%
Other values (26) 30
 
11.2%
Hangul
ValueCountFrequency (%)
이 176
 
5.4%
주 175
 
5.4%
스 171
 
5.3%
사 163
 
5.0%
회 154
 
4.7%
식 152
 
4.7%
아 72
 
2.2%
트 61
 
1.9%
에 60
 
1.9%
리 47
 
1.4%
Other values (352) 2012
62.0%

대표자성명
Text

Distinct501
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-05-11T14:41:15.605944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length3
Mean length3.2821012
Min length2

Characters and Unicode

Total characters1687
Distinct characters189
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique488 ?
Unique (%)94.9%

Sample

1st row박신후
2nd row정희범
3rd row이건호,안상원
4th row변준원
5th row이승준
ValueCountFrequency (%)
서예원 2
 
0.4%
이선우 2
 
0.4%
이성주 2
 
0.4%
이정석 2
 
0.4%
이승호 2
 
0.4%
김영환 2
 
0.4%
김명현 2
 
0.4%
훈 2
 
0.4%
김동현 2
 
0.4%
박현수 2
 
0.4%
Other values (513) 517
96.3%
2024-05-11T14:41:16.313100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 117
 
6.9%
이 83
 
4.9%
영 57
 
3.4%
정 47
 
2.8%
박 45
 
2.7%
진 39
 
2.3%
성 35
 
2.1%
현 31
 
1.8%
상 30
 
1.8%
석 29
 
1.7%
Other values (179) 1174
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1614
95.7%
Space Separator 27
 
1.6%
Uppercase Letter 27
 
1.6%
Other Punctuation 19
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 117
 
7.2%
이 83
 
5.1%
영 57
 
3.5%
정 47
 
2.9%
박 45
 
2.8%
진 39
 
2.4%
성 35
 
2.2%
현 31
 
1.9%
상 30
 
1.9%
석 29
 
1.8%
Other values (161) 1101
68.2%
Uppercase Letter
ValueCountFrequency (%)
N 4
14.8%
A 3
11.1%
R 3
11.1%
O 3
11.1%
E 2
 
7.4%
B 2
 
7.4%
I 2
 
7.4%
S 1
 
3.7%
P 1
 
3.7%
K 1
 
3.7%
Other values (5) 5
18.5%
Other Punctuation
ValueCountFrequency (%)
, 16
84.2%
/ 3
 
15.8%
Space Separator
ValueCountFrequency (%)
27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1614
95.7%
Common 46
 
2.7%
Latin 27
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 117
 
7.2%
이 83
 
5.1%
영 57
 
3.5%
정 47
 
2.9%
박 45
 
2.8%
진 39
 
2.4%
성 35
 
2.2%
현 31
 
1.9%
상 30
 
1.9%
석 29
 
1.8%
Other values (161) 1101
68.2%
Latin
ValueCountFrequency (%)
N 4
14.8%
A 3
11.1%
R 3
11.1%
O 3
11.1%
E 2
 
7.4%
B 2
 
7.4%
I 2
 
7.4%
S 1
 
3.7%
P 1
 
3.7%
K 1
 
3.7%
Other values (5) 5
18.5%
Common
ValueCountFrequency (%)
27
58.7%
, 16
34.8%
/ 3
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1614
95.7%
ASCII 73
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 117
 
7.2%
이 83
 
5.1%
영 57
 
3.5%
정 47
 
2.9%
박 45
 
2.8%
진 39
 
2.4%
성 35
 
2.2%
현 31
 
1.9%
상 30
 
1.9%
석 29
 
1.8%
Other values (161) 1101
68.2%
ASCII
ValueCountFrequency (%)
27
37.0%
, 16
21.9%
N 4
 
5.5%
/ 3
 
4.1%
A 3
 
4.1%
R 3
 
4.1%
O 3
 
4.1%
E 2
 
2.7%
B 2
 
2.7%
I 2
 
2.7%
Other values (8) 8
 
11.0%

설립일자
Date

Distinct484
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
Minimum1974-03-21 00:00:00
Maximum2019-12-10 00:00:00
2024-05-11T14:41:16.815198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:17.047625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

정규직수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct77
Distinct (%)55.8%
Missing376
Missing (%)73.2%
Infinite0
Infinite (%)0.0%
Mean54.927536
Minimum8
Maximum337
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-05-11T14:41:17.309230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile12.85
Q122
median35
Q367.75
95-th percentile143.6
Maximum337
Range329
Interquartile range (IQR)45.75

Descriptive statistics

Standard deviation55.812072
Coefficient of variation (CV)1.0161037
Kurtosis9.949009
Mean54.927536
Median Absolute Deviation (MAD)17
Skewness2.8186197
Sum7580
Variance3114.9874
MonotonicityNot monotonic
2024-05-11T14:41:17.560049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18 7
 
1.4%
35 7
 
1.4%
16 6
 
1.2%
14 5
 
1.0%
26 5
 
1.0%
37 4
 
0.8%
47 4
 
0.8%
21 4
 
0.8%
27 4
 
0.8%
25 3
 
0.6%
Other values (67) 89
 
17.3%
(Missing) 376
73.2%
ValueCountFrequency (%)
8 3
0.6%
10 1
 
0.2%
11 1
 
0.2%
12 2
 
0.4%
13 2
 
0.4%
14 5
1.0%
15 1
 
0.2%
16 6
1.2%
18 7
1.4%
19 1
 
0.2%
ValueCountFrequency (%)
337 1
0.2%
330 1
0.2%
284 1
0.2%
215 1
0.2%
199 1
0.2%
174 1
0.2%
147 1
0.2%
143 1
0.2%
131 1
0.2%
130 1
0.2%

비정규직수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing514
Missing (%)100.0%
Memory size4.6 KiB

직원수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct78
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.747082
Minimum0
Maximum337
Zeros376
Zeros (%)73.2%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-05-11T14:41:17.790868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q313.75
95-th percentile82.35
Maximum337
Range337
Interquartile range (IQR)13.75

Descriptive statistics

Standard deviation37.756817
Coefficient of variation (CV)2.5602908
Kurtosis27.751765
Mean14.747082
Median Absolute Deviation (MAD)0
Skewness4.5573123
Sum7580
Variance1425.5772
MonotonicityNot monotonic
2024-05-11T14:41:18.012428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 376
73.2%
35 7
 
1.4%
18 7
 
1.4%
16 6
 
1.2%
14 5
 
1.0%
26 5
 
1.0%
27 4
 
0.8%
21 4
 
0.8%
47 4
 
0.8%
37 4
 
0.8%
Other values (68) 92
 
17.9%
ValueCountFrequency (%)
0 376
73.2%
8 3
 
0.6%
10 1
 
0.2%
11 1
 
0.2%
12 2
 
0.4%
13 2
 
0.4%
14 5
 
1.0%
15 1
 
0.2%
16 6
 
1.2%
18 7
 
1.4%
ValueCountFrequency (%)
337 1
0.2%
330 1
0.2%
284 1
0.2%
215 1
0.2%
199 1
0.2%
174 1
0.2%
147 1
0.2%
143 1
0.2%
131 1
0.2%
130 1
0.2%

업종코드
Real number (ℝ)

MISSING 

Distinct118
Distinct (%)50.2%
Missing279
Missing (%)54.3%
Infinite0
Infinite (%)0.0%
Mean35062.149
Minimum13
Maximum85709
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-05-11T14:41:18.238050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile31.1
Q120461
median29199
Q358221
95-th percentile72121
Maximum85709
Range85696
Interquartile range (IQR)37760

Descriptive statistics

Standard deviation22417.514
Coefficient of variation (CV)0.63936509
Kurtosis-0.98977119
Mean35062.149
Median Absolute Deviation (MAD)18018
Skewness0.059651242
Sum8239605
Variance5.0254493 × 108
MonotonicityNot monotonic
2024-05-11T14:41:18.444371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58222 21
 
4.1%
58221 13
 
2.5%
33999 10
 
1.9%
62010 9
 
1.8%
62021 8
 
1.6%
27199 7
 
1.4%
20423 5
 
1.0%
33 5
 
1.0%
32 4
 
0.8%
27 4
 
0.8%
Other values (108) 149
29.0%
(Missing) 279
54.3%
ValueCountFrequency (%)
13 3
0.6%
26 2
 
0.4%
27 4
0.8%
28 2
 
0.4%
29 1
 
0.2%
32 4
0.8%
33 5
1.0%
41 1
 
0.2%
46 1
 
0.2%
62 2
 
0.4%
ValueCountFrequency (%)
85709 1
 
0.2%
84119 1
 
0.2%
75992 1
 
0.2%
73909 3
0.6%
73209 1
 
0.2%
73202 2
0.4%
72122 1
 
0.2%
72121 3
0.6%
71531 1
 
0.2%
71400 1
 
0.2%

업종코드명
Text

Distinct191
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-05-11T14:41:18.867494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length11.346304
Min length2

Characters and Unicode

Total characters5832
Distinct characters226
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique135 ?
Unique (%)26.3%

Sample

1st row제조업
2nd row정보통신업
3rd row제조업
4th row제조업
5th row정보통신업
ValueCountFrequency (%)
및 182
 
11.2%
제조업 164
 
10.1%
정보통신업 85
 
5.2%
기타 80
 
4.9%
서비스업 57
 
3.5%
외 44
 
2.7%
소프트웨어 43
 
2.6%
서비스 42
 
2.6%
그 41
 
2.5%
개발 40
 
2.5%
Other values (270) 852
52.3%
2024-05-11T14:41:19.549683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1126
 
19.3%
업 446
 
7.6%
제 244
 
4.2%
기 196
 
3.4%
조 187
 
3.2%
및 187
 
3.2%
스 154
 
2.6%
비 149
 
2.6%
서 123
 
2.1%
, 115
 
2.0%
Other values (216) 2905
49.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4573
78.4%
Space Separator 1126
 
19.3%
Other Punctuation 127
 
2.2%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Decimal Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 446
 
9.8%
제 244
 
5.3%
기 196
 
4.3%
조 187
 
4.1%
및 187
 
4.1%
스 154
 
3.4%
비 149
 
3.3%
서 123
 
2.7%
정 112
 
2.4%
통 111
 
2.4%
Other values (207) 2664
58.3%
Other Punctuation
ValueCountFrequency (%)
, 115
90.6%
. 5
 
3.9%
; 5
 
3.9%
/ 2
 
1.6%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
1126
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4573
78.4%
Common 1259
 
21.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 446
 
9.8%
제 244
 
5.3%
기 196
 
4.3%
조 187
 
4.1%
및 187
 
4.1%
스 154
 
3.4%
비 149
 
3.3%
서 123
 
2.7%
정 112
 
2.4%
통 111
 
2.4%
Other values (207) 2664
58.3%
Common
ValueCountFrequency (%)
1126
89.4%
, 115
 
9.1%
. 5
 
0.4%
; 5
 
0.4%
/ 2
 
0.2%
) 2
 
0.2%
( 2
 
0.2%
1 1
 
0.1%
2 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4573
78.4%
ASCII 1259
 
21.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1126
89.4%
, 115
 
9.1%
. 5
 
0.4%
; 5
 
0.4%
/ 2
 
0.2%
) 2
 
0.2%
( 2
 
0.2%
1 1
 
0.1%
2 1
 
0.1%
Hangul
ValueCountFrequency (%)
업 446
 
9.8%
제 244
 
5.3%
기 196
 
4.3%
조 187
 
4.1%
및 187
 
4.1%
스 154
 
3.4%
비 149
 
3.3%
서 123
 
2.7%
정 112
 
2.4%
통 111
 
2.4%
Other values (207) 2664
58.3%

주소
Text

UNIQUE 

Distinct514
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-05-11T14:41:20.077759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length46
Mean length28.817121
Min length11

Characters and Unicode

Total characters14812
Distinct characters381
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique514 ?
Unique (%)100.0%

Sample

1st row서울시 성동구 성수이로22길61 5층
2nd row서울시 강남구 테헤란로 427, 16층
3rd row서울시 강남구 테헤란로 22길 9, 3,4,6층(역삼동, 아름다운빌딩)
4th row서울시 강남구 논현로 805, B1~1F(신사동)
5th row서울시 강서구 마곡중앙4로 18, B동 720호
ValueCountFrequency (%)
서울시 278
 
9.7%
강남구 100
 
3.5%
금천구 89
 
3.1%
구로구 59
 
2.1%
서울특별시 52
 
1.8%
서초구 47
 
1.6%
송파구 41
 
1.4%
성동구 41
 
1.4%
디지털로 34
 
1.2%
영등포구 32
 
1.1%
Other values (1233) 2102
73.1%
2024-05-11T14:41:20.840146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2434
 
16.4%
1 742
 
5.0%
구 630
 
4.3%
로 608
 
4.1%
서 460
 
3.1%
, 422
 
2.8%
2 412
 
2.8%
0 370
 
2.5%
울 346
 
2.3%
시 345
 
2.3%
Other values (371) 8043
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8145
55.0%
Decimal Number 3080
 
20.8%
Space Separator 2434
 
16.4%
Other Punctuation 428
 
2.9%
Open Punctuation 206
 
1.4%
Close Punctuation 206
 
1.4%
Uppercase Letter 194
 
1.3%
Dash Punctuation 55
 
0.4%
Lowercase Letter 46
 
0.3%
Math Symbol 18
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 630
 
7.7%
로 608
 
7.5%
서 460
 
5.6%
울 346
 
4.2%
시 345
 
4.2%
동 308
 
3.8%
호 239
 
2.9%
층 221
 
2.7%
길 212
 
2.6%
강 162
 
2.0%
Other values (310) 4614
56.6%
Uppercase Letter
ValueCountFrequency (%)
C 21
10.8%
S 21
10.8%
A 20
10.3%
B 17
 
8.8%
T 15
 
7.7%
I 13
 
6.7%
K 11
 
5.7%
E 11
 
5.7%
M 8
 
4.1%
V 8
 
4.1%
Other values (13) 49
25.3%
Lowercase Letter
ValueCountFrequency (%)
e 8
17.4%
n 8
17.4%
o 4
8.7%
i 4
8.7%
b 3
 
6.5%
r 3
 
6.5%
a 3
 
6.5%
k 2
 
4.3%
t 2
 
4.3%
s 2
 
4.3%
Other values (7) 7
15.2%
Decimal Number
ValueCountFrequency (%)
1 742
24.1%
2 412
13.4%
0 370
12.0%
3 341
11.1%
4 265
 
8.6%
6 221
 
7.2%
5 218
 
7.1%
8 184
 
6.0%
7 181
 
5.9%
9 146
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 422
98.6%
/ 2
 
0.5%
& 2
 
0.5%
# 1
 
0.2%
. 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 17
94.4%
+ 1
 
5.6%
Space Separator
ValueCountFrequency (%)
2434
100.0%
Open Punctuation
ValueCountFrequency (%)
( 206
100.0%
Close Punctuation
ValueCountFrequency (%)
) 206
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 55
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8145
55.0%
Common 6427
43.4%
Latin 240
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 630
 
7.7%
로 608
 
7.5%
서 460
 
5.6%
울 346
 
4.2%
시 345
 
4.2%
동 308
 
3.8%
호 239
 
2.9%
층 221
 
2.7%
길 212
 
2.6%
강 162
 
2.0%
Other values (310) 4614
56.6%
Latin
ValueCountFrequency (%)
C 21
 
8.8%
S 21
 
8.8%
A 20
 
8.3%
B 17
 
7.1%
T 15
 
6.2%
I 13
 
5.4%
K 11
 
4.6%
E 11
 
4.6%
e 8
 
3.3%
M 8
 
3.3%
Other values (30) 95
39.6%
Common
ValueCountFrequency (%)
2434
37.9%
1 742
 
11.5%
, 422
 
6.6%
2 412
 
6.4%
0 370
 
5.8%
3 341
 
5.3%
4 265
 
4.1%
6 221
 
3.4%
5 218
 
3.4%
( 206
 
3.2%
Other values (11) 796
 
12.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8145
55.0%
ASCII 6667
45.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2434
36.5%
1 742
 
11.1%
, 422
 
6.3%
2 412
 
6.2%
0 370
 
5.5%
3 341
 
5.1%
4 265
 
4.0%
6 221
 
3.3%
5 218
 
3.3%
( 206
 
3.1%
Other values (51) 1036
15.5%
Hangul
ValueCountFrequency (%)
구 630
 
7.7%
로 608
 
7.5%
서 460
 
5.6%
울 346
 
4.2%
시 345
 
4.2%
동 308
 
3.8%
호 239
 
2.9%
층 221
 
2.7%
길 212
 
2.6%
강 162
 
2.0%
Other values (310) 4614
56.6%

년도_정렬
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018.5195
Minimum2016
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-05-11T14:41:21.019521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2016
5-th percentile2016
Q12016
median2019
Q32020
95-th percentile2023
Maximum2023
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.233148
Coefficient of variation (CV)0.0011063297
Kurtosis-0.8616952
Mean2018.5195
Median Absolute Deviation (MAD)2
Skewness0.35112163
Sum1037519
Variance4.9869502
MonotonicityDecreasing
2024-05-11T14:41:21.220838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2016 182
35.4%
2019 97
18.9%
2020 95
18.5%
2018 48
 
9.3%
2023 44
 
8.6%
2021 43
 
8.4%
2017 5
 
1.0%
ValueCountFrequency (%)
2016 182
35.4%
2017 5
 
1.0%
2018 48
 
9.3%
2019 97
18.9%
2020 95
18.5%
2021 43
 
8.4%
2023 44
 
8.6%
ValueCountFrequency (%)
2023 44
 
8.6%
2021 43
 
8.4%
2020 95
18.5%
2019 97
18.9%
2018 48
 
9.3%
2017 5
 
1.0%
2016 182
35.4%

등록일시
Date

MISSING 

Distinct53
Distinct (%)16.0%
Missing182
Missing (%)35.4%
Memory size4.1 KiB
Minimum2017-07-04 11:16:46
Maximum2023-01-13 14:30:22
2024-05-11T14:41:21.439492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:21.678283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수정일시
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing514
Missing (%)100.0%
Memory size4.6 KiB

Interactions

2024-05-11T14:41:12.187269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:10.434738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:11.038286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:11.718967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:12.336243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:10.621315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:11.190750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:11.843401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:12.505582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:10.760813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:11.382504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:11.948369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:12.664775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:10.879316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:11.527372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:41:12.053360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T14:41:21.842477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기업구분기업구분명정규직수직원수업종코드년도_정렬등록일시
기업구분1.0001.000NaN0.2870.626NaNNaN
기업구분명1.0001.000NaN0.2870.626NaNNaN
정규직수NaNNaN1.0000.997NaN0.2530.253
직원수0.2870.2870.9971.000NaN0.5270.000
업종코드0.6260.626NaNNaN1.0000.0000.990
년도_정렬NaNNaN0.2530.5270.0001.0001.000
등록일시NaNNaN0.2530.0000.9901.0001.000
2024-05-11T14:41:22.014558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기업구분기업구분명
기업구분1.0000.996
기업구분명0.9961.000
2024-05-11T14:41:22.160065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정규직수직원수업종코드년도_정렬기업구분기업구분명
정규직수1.0001.000NaN0.1251.0001.000
직원수1.0001.000NaN0.5990.2850.285
업종코드NaNNaN1.0000.3690.4770.477
년도_정렬0.1250.5990.3691.0000.9950.995
기업구분1.0000.2850.4770.9951.0000.996
기업구분명1.0000.2850.4770.9950.9961.000

Missing values

2024-05-11T14:41:12.941450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T14:41:13.237957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-11T14:41:13.424253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

기업구분기업구분명업체명대표자성명설립일자정규직수비정규직수직원수업종코드업종코드명주소년도_정렬등록일시수정일시
0ssc서울형 강소기업㈜롤리조쓰컴퍼니박신후2018-08-01<NA><NA>0<NA>제조업서울시 성동구 성수이로22길61 5층20232023-01-13 14:30:22.0<NA>
1ssc서울형 강소기업㈜인티그레이션정희범2019-02-01<NA><NA>0<NA>정보통신업서울시 강남구 테헤란로 427, 16층20232023-01-13 14:30:22.0<NA>
2ssc서울형 강소기업㈜샐러디이건호,안상원2015-04-07<NA><NA>0<NA>제조업서울시 강남구 테헤란로 22길 9, 3,4,6층(역삼동, 아름다운빌딩)20232023-01-13 14:30:22.0<NA>
3ssc서울형 강소기업설로인 주식회사변준원2017-09-08<NA><NA>0<NA>제조업서울시 강남구 논현로 805, B1~1F(신사동)20232023-01-13 14:30:22.0<NA>
4ssc서울형 강소기업㈜테온이승준2019-08-26<NA><NA>0<NA>정보통신업서울시 강서구 마곡중앙4로 18, B동 720호20232023-01-13 14:30:22.0<NA>
5ssc서울형 강소기업주식회사 크몽박현호2012-06-01<NA><NA>0<NA>정보통신업서울시 서초구 사임당로 157, 릿타워 3층20232023-01-13 14:30:22.0<NA>
6ssc서울형 강소기업주식회사 올라핀테크김상수2019-12-10<NA><NA>0<NA>정보통신업서울시 강남구 선릉로615, 1층20232023-01-13 14:30:22.0<NA>
7ssc서울형 강소기업(주)해빗팩토리이동익,정윤호2016-01-08<NA><NA>0<NA>정보통신업서울시 용산구 서빙고로 17 센트럴파크타워 23층 2301호20232023-01-13 14:30:22.0<NA>
8ssc서울형 강소기업주식회사 클래스101공대선2015-09-01<NA><NA>0<NA>정보통신업서울시 강남구 테헤란로 302, 1-11층, 13층20232023-01-13 14:30:22.0<NA>
9ssc서울형 강소기업주식회사 무로코퍼레이션전병민2019-04-12<NA><NA>0<NA>도매 및 소매업서울시 강남구 테헤란로 33길 34 B1F~2F20232023-01-13 14:30:22.0<NA>
기업구분기업구분명업체명대표자성명설립일자정규직수비정규직수직원수업종코드업종코드명주소년도_정렬등록일시수정일시
504src하이서울브랜드 기업㈜제이앤케이사이언스조금용2007-06-22<NA><NA>046109상품 종합 중개업서초구 방배로 143, 402(방배동, 정진빌딩)2016<NA><NA>
505src하이서울브랜드 기업㈜뮈샤김정주2007-05-19<NA><NA>046492시계 및 귀금속제품 도매업강남구 도산대로67길 13-5 뮈샤빌딩2016<NA><NA>
506src하이서울브랜드 기업㈜트레이드월드김영호2005-03-10<NA><NA>073209패션, 섬유류 및 기타 전문 디자인업강남구 강남구 논현로 28길 35 대동빌딩5층2016<NA><NA>
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509src하이서울브랜드 기업슈어엠주식회사백남욱2000-04-01<NA><NA>063정보서비스업송파구 오금로81 송파빌딩 11층2016<NA><NA>
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